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01_​Image_​ReStyling_​Webportal

Image Neuro-Styling

This workflow implements the web based application performing the neuro-styling of an input image.
It requires:
- an input image (a portrait image) to be uploaded in the component "Upload Input Images"
- a style image (pre-loaded) to perform the neuro-styling
- the Style Transfer in python component including the required Python code
The output is the original portrait image with touches of the art masterpiece used for the neuro-styling.

Image preprocessing:- Resize all images in the table- Loop through columns andapply VGG preprocessing(color channel normalisationand reordering) Inputs:- Configuration for the styling algorithm- CSS style for web pages- Upload portrait and select art style images Display styled images Transfer style from the art imageto the portrait using Keras in apython script. Reverse image preprocessing:- Restore original color channel normalisationand order Image Neuro-StylingThis workflow implements the web based application performing the neuro-styling of an input image. It requires: - an input image (a portrait image) to be uploaded in the component "Upload Input Images" - a style image (pre-loaded) to perform the neuro-styling - the Style Transfer in python component including the required Python codeThe output is the original portrait image with touches of the art masterpiece used for the neuro-styling. Warning: This workflow requires KNIME Deep Learning and python extensions installed. Follow instructions relevant for the Keras extension installation in:https://docs.knime.com/2021-12/deep_learning_installation_guide/index.html#keras-integration Loop over rowsand dostyle transferusing imagesin each rowResize images,normalise andreordercolor channelsCSS styleand algorithmsettingsBuild a web viewto displaystyled images and to let the userdownload themRestorenormalisation andorder ofcolor channelsColumn fordeprocessingUpload a portraitand select artimage to extract styleStyle Transferin python Image preprocessing Inject Variables(Data) Configurationand Styling Displaystyled images Image deprocessingfor VGG StringConfiguration Upload input images Image preprocessing:- Resize all images in the table- Loop through columns andapply VGG preprocessing(color channel normalisationand reordering) Inputs:- Configuration for the styling algorithm- CSS style for web pages- Upload portrait and select art style images Display styled images Transfer style from the art imageto the portrait using Keras in apython script. Reverse image preprocessing:- Restore original color channel normalisationand order Image Neuro-StylingThis workflow implements the web based application performing the neuro-styling of an input image. It requires: - an input image (a portrait image) to be uploaded in the component "Upload Input Images" - a style image (pre-loaded) to perform the neuro-styling - the Style Transfer in python component including the required Python codeThe output is the original portrait image with touches of the art masterpiece used for the neuro-styling. Warning: This workflow requires KNIME Deep Learning and python extensions installed. Follow instructions relevant for the Keras extension installation in:https://docs.knime.com/2021-12/deep_learning_installation_guide/index.html#keras-integration Loop over rowsand dostyle transferusing imagesin each rowResize images,normalise andreordercolor channelsCSS styleand algorithmsettingsBuild a web viewto displaystyled images and to let the userdownload themRestorenormalisation andorder ofcolor channelsColumn fordeprocessingUpload a portraitand select artimage to extract styleStyle Transferin python Image preprocessing Inject Variables(Data) Configurationand Styling Displaystyled images Image deprocessingfor VGG StringConfiguration Upload input images

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: Adrian Nembach
Created at: 2019-03-14
On NodePit since: 2019-07-12
Last update: 2024-04-18
Created with KNIME version: v4.5.2

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